Priyank Thakkar

Dr. Priyank Thakkar

orcid

Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2015 in Expert Systems with Applications
Verified
Journal Article
Closed access
JPJigar Patel
Jigar Patel
SSSahil Shah
Sahil Shah
PTPriyank Thakkar
Priyank Thakkar
Ketan KotechaKetan Kotecha
Ketan Kotecha

1 March 2015 in Expert Systems with Applications
Verified
Journal Article
Closed access
JPJigar Patel
Jigar Patel
SSSahil Shah
Sahil Shah
PTPriyank Thakkar
Priyank Thakkar
Ketan KotechaKetan Kotecha
Ketan Kotecha

15 December 2018
Verified
Book Chapter
Closed access
PDF file
PTPriyank Thakkar
Priyank Thakkar
KVKrunal Varma
Krunal Varma
VUVijay Ukani
Vijay Ukani
SMSapan Mankad
Sapan Mankad
STSudeep Tanwar
Sudeep Tanwar

25 December 2023 in IEEE Access
Verified
Journal Article
Open access
AMAryan Alpesh Mehta
Aryan Alpesh Mehta
APAli Asgar Padaria
Ali Asgar Padaria
DBDwij Jayesh Bavisi
Dwij Jayesh Bavisi
VUVijay Ukani
Vijay Ukani
PTPriyank Thakkar
Priyank Thakkar
Ajith AbrahamAjith Abraham
Ajith Abraham
Advanced Driver Assistance Systems (ADAS) are advanced technologies that assist drivers with vehicle operation and navigation. Recent improvements and brisk expansion in the ADAS market, as well as an increase in the frequency of incidents such as sensor spoofing, communication interruption etc., in autonomous vehicles (AVs), have raised the need to research ADAS security technology. The security issues raised by incorporating these technologies into automobiles must be addressed to protect the privacy and safety of passengers and other road users. As a result, the purpose of this research is to investigate the security issues that arise from the integration of ADAS technologies. Addressing these challenges holds the potential to establish a foundation for enhanced safety and dependability within transportation networks amidst the ongoing advancements in vehicle technology. This paper starts by describing the vulnerabilities, threats, assaults, and defense mechanisms of the ADAS. It then delves into the attacks and countermeasures in three categories, namely VANET, Hardware, and Adversarial attacks. VANET attacks encompass threats targeting Vehicular Ad Hoc Networks, aiming to disrupt communication among vehicles or between vehicles and infrastructure. Hardware attacks focus on vulnerabilities within the physical components of ADAS, including sensors, processors, or communication modules. Adversarial attacks involve deliberate manipulations or perturbations introduced into machine learning models or algorithms utilized within ADAS. These attacks aim to deceive or undermine the functionality of AI-based systems, causing misclassification, compromising system integrity, and posing risks to user safety by exploiting vulnerabilities in the AI decision-making process. Finally, this study highlights potential areas for future research, such as the utilization of artificial intelligence (AI), the necessity of industry-wide standardization, and recommends specific future work tailored to each attack described in the corresponding sections.

10 February 2024 in Engineering Applications of Artificial Intelligence
Verified
Journal Article
Closed access
RPRonakkumar Patel
Ronakkumar Patel
PTPriyank Thakkar
Priyank Thakkar
VUVijay Ukani
Vijay Ukani

28 December 2021 in Journal of Forecasting
Verified
Journal Article
Closed access
PDF file
YTYash Thesia
Yash Thesia
VOVidhey Oza
Vidhey Oza
PTPriyank Thakkar
Priyank Thakkar